Resum:

Background: The recent increase in human polymorphism data, together with the availability of genome sequences from several primate species, provides an unprecedented opportunity to investigate how natural selection has shaped human evolution. Results: We compared human branch-specific substitutions with variation data in the current human population to measure the impact of adaptive evolution on human protein coding genes. The use of single nucleotide polymorphisms (SNPs) with high derived allele ...

Background: The recent increase in human polymorphism data, together with the availability of genome sequences from several primate species, provides an unprecedented opportunity to investigate how natural selection has shaped human evolution. Results: We compared human branch-specific substitutions with variation data in the current human population to measure the impact of adaptive evolution on human protein coding genes. The use of single nucleotide polymorphisms (SNPs) with high derived allele frequencies (DAFs) minimized the influence of segregating slightly deleterious mutations and improved the estimation of the number of adaptive sites. Using DAF ≥ 60% we showed that the proportion of adaptive substitutions is 0.2% in the complete gene set. However, the percentage rose to 40% when we focused on genes that are specifically accelerated in the human branch with respect to the chimpanzee branch, or on genes that show signatures of adaptive selection at the codon level by the maximum likelihood based branch-site test. In general, neural genes are enriched in positive selection signatures. Genes with multiple lines of evidence of positive selection include taxilin beta, which is involved in motor nerve regeneration and syntabulin, and is required for the formation of new presynaptic boutons. Conclusions: We combined several methods to detect adaptive evolution in human coding sequences at a genome-wide level. The use of variation data, in addition to sequence divergence information, uncovered previously undetected positive selection signatures in neural genes.